Search Results - (( data detection sensor algorithm ) OR ( java application path algorithm ))

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    Wearable based-sensor fall detection system using machine learning algorithm by Ishak, Anis Nadia, Habaebi, Mohamed Hadi, Yusoff, Siti Hajar, Islam, Md. Rafiqul

    Published 2021
    “…In this project, a wearable sensor-based fall detection system using a machine-learning algorithm had been developed. …”
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    Proceeding Paper
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    Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

    Published 2004
    “…Misuse detection algorithms model know attack behavior. They compare sensor data to attack patterns learned from the training data. …”
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    Thesis
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    Deforestation detection in Kinabalu Area, Sabah, Malaysia by using multi-sensor remote sensing approach by Phua, Mui How, Tsuyuki, Satoshi

    Published 2004
    “…Multi-sensor satellite data of Landsat-MSS of 1973 and Landsat-TM of 1991 and 1996 were employed. …”
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    Article
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    Faulty sensor detection using data correlation of multivariant sensor reading in smart agriculture with IOT by Malik, Ahmed Dhahir

    Published 2019
    “…This thesis proposes to design a Faulty Sensor Detection Mechanism using the data correlation method of multivariate sensors. …”
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    Thesis
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    A systematic literature review on outlier detection in wireless sensor networks by Safaei, Mahmood, Asadi, Shahla, Driss, Maha, Boulila, Wadii, Alsaeedi, Abdullah, Chizari, Hassan, Abdullah, Rusli, Safaei, Mitra

    Published 2020
    “…Therefore, an efficient local/distributed data processing algorithm is needed to ensure: (1) the extraction of precise and reliable values from noisy readings; (2) the detection of anomalies from data reported by sensors; and (3) the identification of outlier sensors in a WSN. …”
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    Article
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    A study on advanced statistical analysis for network anomaly detection by Ngadi, Md. Asri, Idris, Mohd. Yazid, Abdullah, Abd. Hanan

    Published 2005
    “…Misuse detection algorithms model know attack behavior. They compare sensor data to attack patterns learned from the training data. …”
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    Monograph
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    Data redundancy reduction scheme for data aggregation in wireless sensor network by Adawy, Mohammad Ibrahim

    Published 2020
    “…Also, the results show that the proposed Anomaly Detection (AD) outperforms FTDA in terms of aggregated data accuracy in which the AD conserved approximately, 59.5% of aggregated data accuracy for event compared with FTDA algorithm which conserved 54.25% of aggregated data accuracy for event. …”
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    Thesis
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    Autonomous road roundabout detection and navigation system for smart vehicles and cities using laser simulator–fuzzy logic algorithms and sensor fusion by Ali, Mohammed A. H., Musa, Mailah, Jabbar, Waheb A., Moiduddin, Khaja, Ameen, Wadea, Alkhalefah, Hisham

    Published 2020
    “…A real-time roundabout detection and navigation system for smart vehicles and cities using laser simulator–fuzzy logic algorithms and sensor fusion in a road environment is presented in this paper. …”
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    Article
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    Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor / Muhammad Nasrul Hakim Adenan by Adenan, Muhammad Nasrul Hakim

    Published 2013
    “…Membrane acts as selector for the ions. The sensor detects the ions and converts it into electrical signal. …”
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    Thesis
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    Multi-sensor fusion and deep learning framework for automatic human activity detection and health monitoring using motion sensor data / Henry Friday Nweke by Henry Friday , Nweke

    Published 2019
    “…Over the years, various machine learning methods have been proposed to analyse collected sensor data to infer certain activity details. However, analysis of mobile and wearable sensor data for human activity detection is still very challenging. …”
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    Thesis
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    Collision avoidance algorithm design for UAV base on parametric theorem and circle overlapping method / Nur Fadzilah Mohamad Radzi by Nur Fadzilah, Mohamad Radzi

    Published 2013
    “…Then, a collision detection algorithm is developed to calculate the potential of collision in future. …”
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    Thesis
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    Revolutionizing Perimeter Intrusion Detection: A Machine Learning-Driven Approach with Curated Dataset Generation for Enhanced Security by Pitafi, S., Anwar, T., Dewa Made Widia, I., Yimwadsana, B.

    Published 2023
    “…After collecting the data from above mentioned sensors we applied machine learning algorithms DBSCAN to cluster the data points and K-NN classification to classify those clusters in one-dimensional data, but the results were not much satisfying. …”
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    Article
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    Smart appointment organizer for mobile application / Mohd Syafiq Adam by Adam, Mohd Syafiq

    Published 2009
    “…In creating this application, NetBeans IDE 6.5and Java Micro Edition (Java ME) are used. …”
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    Thesis
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    Performance comparison of classification algorithms for EEG-based remote epileptic seizure detection in wireless sensor networks by Abualsaud, Khalid, Mahmuddin, Massudi, Saleh, Mohammad, Mohamed, Amr

    Published 2014
    “…Identification of epileptic seizure remotely by analyzing the electroencephalography (EEG) signal is very important for scalable sensor-based health systems.Classification is the most important technique for wide-ranging applications to categorize the items according to its features with respect to predefined set of classes.In this paper, we conduct a performance evaluation based on the noiseless and noisy EEG-based epileptic seizure data using various classification algorithms including BayesNet, DecisionTable, IBK, J48/C4.5, and VFI.The reconstructed and noisy EEG data are decomposed with discrete cosine transform into several sub-bands.In addition, some of statistical features are extracted from the wavelet coefficients to represent the whole EEG data inputs into the classifiers.Benchmark on widely used dataset is utilized for automatic epileptic seizure detection including both normal and epileptic EEG datasets.The classification accuracy results confirm that the selected classifiers have greater potentiality to identify the noisy epileptic disorders.…”
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    Conference or Workshop Item